Assistant Professor
Department of Computer Science
University of Toronto
I’m an Assistant Professor in the Department of Computer Science at the University of Toronto, a faculty affiliate at the Vector Institute, a faculty fellow at AXL, and a founding member of the Toronto Computational Imaging Group.
My research focuses on physically based intelligent sensing: a paradigm that combines physically based models, signal processing, and artificial intelligence to break the limits of current sensing systems and re-think how we reconstruct the world from captured visual information. Recent work in my group spans methods that recover geometry and material properties from ultrafast videos of light propagation; large-scale generative models that tackle ill-posed problems in video and 4D reconstruction; and emerging sensing systems that exploit individual photon detections and the coherent properties of light to unlock new capabilities in imaging and 3D reconstruction. My work contributes broadly to applications across computational imaging, computer graphics, computer vision, and robotics.
Three papers accepted recently! Non-line-of-sight Surface Reconstruction Using the Directional Light-cone Transform (Oral @ CVPR 2020), SPADnet: deep RGB-SPAD sensor fusion assisted by monocular depth estimation (Optics Express), and Deep Adaptive LiDAR: End-to-end Optimization of Sampling and Depth Completion at Low Sampling Rates (ICCP 2020).
Two papers accepted! Acoustic Non-Line-of-Sight Imaging was accepted as an oral to CVPR, and Wave-Based Non-Line-of-Sight Imaging Using Fast f-k Migration was accepted to SIGGRAPH.